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update setup guide
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docs/tutorials/mcp.md

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## I just want to set up the MCP
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First, you'll need to set up the GUM in general, and have it build some sense of your context. To do this, follow the instructions on [the front page here.](../index.md) You'll also need a client that supports MCP (e.g. the Claude Desktop app).
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First, you'll need to set up the GUM in general and have it build some sense of your context. To do this, follow the instructions on [the front page here.](../index.md). You'll also need a client that supports MCP. One example client is the MacOS Claude Desktop app, which you can download [here](https://claude.ai/download). The Claude desktop app requires the uv package manager for MCP, so you'll need to follow [the instructions on the uv website](https://docs.astral.sh/uv/getting-started/installation/) (or simply ```brew install uv```).
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Once you're done with that, just clone the [MCP Repository](https://github.com/GeneralUserModels/gumcp) and run the following:
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```bash
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> git clone [email protected]:GeneralUserModels/gumcp.git
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> cd gumcp
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> # maybe create a python environment :)
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> pip install --editable .
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```
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Once you're in the gumcp folder, create a .env file with your environment variables. All you need is a user name in the file (e.g.```USER_NAME="Omar Shaikh"```). In sum, the contents of your .env file looks something like this:
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In the gumcp folder, create a .env file with your environment variables. All you need is a user name in the file (e.g.```USER_NAME="Omar Shaikh"```). In sum, the contents of your .env file looks something like this:
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```bash
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USER_NAME="Omar Shaikh"
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Finally, install the MCP client, pointing to the .env file:
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```bash
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> mcp install server.py -f .env --with gum-ai
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> uv run mcp install server.py -f .env --with gum-ai
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```
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The MCP should then be enabled in the Claude app!
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!!! note "The MCP **only** connects clients like the Claude app to the GUM."
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Simply enabling the MCP does not mean the GUM is learning. You still need to have the background GUM process running to build the underlying database of propositions (e.g. from the instructions on [the front page here.](../index.md))
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## Tutorial
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(coming soon: a walkthough on how this was built!)

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